Tag
#MIT Schwarzman College of Computing
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Can robots learn from machine dreams?
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3 Questions: Inverting the problem of design
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A causal theory for studying the cause-and-effect relationships of genes
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A portable light system that can digitize everyday objects
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Nanoscale transistors could enable more efficient electronics
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A faster, better way to train general-purpose robots
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Making it easier to verify an AI model’s responses
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Combining next-token prediction and video diffusion in computer vision and robotics
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How AI is improving simulations with smarter sampling techniques
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AI pareidolia: Can machines spot faces in inanimate objects?
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Helping robots zero in on the objects that matter
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New security protocol shields data from attackers during cloud-based computation
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3 Questions: Should we label AI systems like we do prescription drugs?
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Study: AI could lead to inconsistent outcomes in home surveillance
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Enhancing LLM collaboration for smarter, more efficient solutions
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A fast and flexible approach to help doctors annotate medical scans
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A framework for solving parabolic partial differential equations
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LLMs develop their own understanding of reality as their language abilities improve
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MIT researchers use large language models to flag problems in complex systems
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Helping robots practice skills independently to adapt to unfamiliar environments
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Precision home robots learn with real-to-sim-to-real
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Method prevents an AI model from being overconfident about wrong answers
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Study: When allocating scarce resources with AI, randomization can improve fairness
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MIT researchers advance automated interpretability in AI models
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AI model identifies certain breast tumor stages likely to progress to invasive cancer
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Creating and verifying stable AI-controlled systems in a rigorous and flexible way
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AI method radically speeds predictions of materials’ thermal properties
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How to assess a general-purpose AI model’s reliability before it’s deployed
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Marking a milestone: Dedication ceremony celebrates the new MIT Schwarzman College of Computing building
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Reasoning skills of large language models are often overestimated
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When to trust an AI model
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MIT researchers introduce generative AI for databases
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Helping nonexperts build advanced generative AI models
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MIT-Takeda Program wraps up with 16 publications, a patent, and nearly two dozen projects completed
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Understanding the visual knowledge of language models
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A smarter way to streamline drug discovery
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Technique improves the reasoning capabilities of large language models
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Researchers use large language models to help robots navigate
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New algorithm discovers language just by watching videos
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A technique for more effective multipurpose robots
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Looking for a specific action in a video? This AI-based method can find it for you
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Controlled diffusion model can change material properties in images
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2024 MAD Design Fellows announced
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Scientists use generative AI to answer complex questions in physics
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Using ideas from game theory to improve the reliability of language models
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The power of App Inventor: Democratizing possibilities for mobile applications
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A better way to control shape-shifting soft robots
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Creating bespoke programming languages for efficient visual AI systems
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Natural language boosts LLM performance in coding, planning, and robotics
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Julie Shah named head of the Department of Aeronautics and Astronautics
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Mapping the brain pathways of visual memorability
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This tiny chip can safeguard user data while enabling efficient computing on a smartphone
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To build a better AI helper, start by modeling the irrational behavior of humans
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3 Questions: Enhancing last-mile logistics with machine learning